As your networks grow, so does their data in the DFP servers. While previously making requests for tens of line items, you now find yourself requesting tens of thousands of line items. Of course, with more data comes more responsibility - your requests are now taking longer and the response sizes have increased accordingly. You notice that some of your requests are now returning with '
ServerError.SERVER_ERROR.' Things might seem hopeless, but don’t panic...
Many of these problems can be solved with pagination! What does this mean from a developer's perspective? In a large number of implementations, what we've noticed is that applications will make requests with empty statements to calls like this:
getCreativesByStatement(" ")
getLineItemsByStatement(" ")
getOrdersByStatement(" ")
getCustomTargetingValuesByStatement(" ")
These requests do not limit the size of the returned result set. In doing so, the applications are asking for the data of every single object belonging to that service. When you’re talking about thousands of line items, each with their own distinct custom targeting, the amount of data will often cause the request to fail.
The fix? When creating PQL statements to query for DFP objects, you’ll find our client libraries all utilize a recommended page size (500) to limit your queries to smaller batches using the 'LIMIT' keyword, which should feel familiar for most who've used SQL. After the first page has returned successfully, you can then use the 'OFFSET' keyword to retrieve each subsequent page until your request returns nothing. If the calls still seem to take a long time to return a page or fail at this point, you can try to use a smaller page size.
If you use pagination to retrieve data, you not only get the benefit of increased reliability, but also protect yourself should something go wrong. Instead of retrying the entire request from the start again, you can simply pick up where you left off.
To see how to implement pagination logic, you can find examples in each of our client libraries:
Ruby
Java
PHP
Python
Dotnet
